CBCT (Cone Beam Computed Tomography) systems are known. For example, U.S. Pat. No. 9,265,475 (Yang) METHOD AND APPARATUS FOR SCATTER CORRECTION FOR CBCT SYSTEM AND CONE-BEAM IMAGE RECONSTRUCTION (incorporated herein in its entirety by reference) wherein the CBCT system describes generation of a 3-D volume image using a set of 2-D (two-dimensional) projection images.
While such systems may have achieved certain degrees of success in their particular applications, there is a need for improvement.
Digital radiographic volume imaging provides three-dimensional (3-D) images that have been reconstructed from a series of 2-D images taken over a succession of angles of the x-ray source relative to the detector. Acquisition of the 2-D projection images used for cone beam CT employs a large-area digital detector, such as a digital radiography (DR) detector that is typically used for conventional single projection radiography.
Computed tomography (CT) systems, such as cone beam computed tomography (CBCT) or cone beam CT systems offer considerable promise as one type of diagnostic tool for providing 3-D volume images. Cone beam CT systems capture volume data sets by using a high frame rate flat panel digital radiography (DR) detector and an x-ray source, typically affixed to a gantry that revolves about the object to be imaged, directing, from various points along its orbit around the subject, a divergent cone beam of x-rays toward the subject. The CBCT system captures projection images throughout the source-detector orbit, for example, with one 2-D projection image at every degree increment of rotation. The projections are then reconstructed into a 3-D volume image using various techniques. Among the most common methods for reconstructing the 3-D volume image are filtered back projection (FBP) approaches. Alternate approaches include iterative processing methods that use a cyclic combination of successive reconstructions and forward projections, filtered upon each iteration in order to reduce error between the reconstruction and the original 2-D projections.
One factor that affects the quality of X-ray imaging overall and volume reconstruction in particular relates to noise inherent to projection image capture. Noise sources include continuously varying error caused by electrical noise or round-off error and discretely varying error resulting from x-ray photon fluctuation. A number of approaches have been proposed for compensating and correcting image noise. However, conventional image acquisition and reconstruction methods leave some room for improvement with respect to image noise. Thus, there would be advantages to volume imaging methods that can reduce noise without increasing dosage requirements.